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A fundamental procedure in the analysis of massive datasets is the construction of similarity graphs. Such graphs play a key role for many downstream tasks, including clustering, classification, graph learning, and nearest neighbor search.…

Machine Learning · Computer Science 2023-01-11 CJ Carey , Jonathan Halcrow , Rajesh Jayaram , Vahab Mirrokni , Warren Schudy , Peilin Zhong

Given a point set $P$ in a metric space and a real number $t \geq 1$, an \emph{oriented $t$-spanner} is an oriented graph $\overrightarrow{G}=(P,\overrightarrow{E})$, where for every pair of distinct points $p$ and $q$ in $P$, the shortest…

Computational Geometry · Computer Science 2024-12-12 Kevin Buchin , Antonia Kalb , Anil Maheshwari , Saeed Odak , Michiel Smid , Carolin Rehs , Sampson Wong

Locally isoperimetric $N$-partitions are partitions of the space $\mathbb R^d$ into $N$ regions with prescribed, finite or infinite measure, which have minimal perimeter (which is the $(d-1)$-dimensional measure of the interfaces between…

Analysis of PDEs · Mathematics 2023-12-22 Matteo Novaga , Emanuele Paolini , Vincenzo Maria Tortorelli

Densest Subgraph Problem (DSP) is an important primitive problem with a wide range of applications, including fraud detection, community detection and DNA motif discovery. Edge-based density is one of the most common metrics in DSP.…

Databases · Computer Science 2023-10-31 Yugao Zhu , Shenghua Liu , Wenjie Feng , Xueqi Cheng

A digraph is connected-homogeneous if any isomorphism between finite connected induced subdigraphs extends to an automorphism of the digraph. We consider locally-finite connected-homogeneous digraphs with more than one end. In the case that…

Combinatorics · Mathematics 2010-11-30 Robert Gray , Rognvaldur G. Moller

We propose a theoretical framework for training Graph Neural Networks (GNNs) on large input graphs via training on small, fixed-size sampled subgraphs. This framework is applicable to a wide range of models, including popular sampling-based…

Machine Learning · Computer Science 2023-10-18 Yeganeh Alimohammadi , Luana Ruiz , Amin Saberi

A spanner graph on a set of points in $R^d$ contains a shortest path between any pair of points with length at most a constant factor of their Euclidean distance. In this paper we investigate new models and aim to interpret why good…

Computational Geometry · Computer Science 2015-05-13 Jie Gao , Dengpan Zhou

Motivated by multipath routing, we introduce a multi-connected variant of spanners. For that purpose we introduce the $p$-multipath cost between two nodes $u$ and $v$ as the minimum weight of a collection of $p$ internally vertex-disjoint…

Networking and Internet Architecture · Computer Science 2011-09-19 Cyril Gavoille , Quentin Godfroy , Laurent Viennot

Given a weighted graph $G(V,E)$ and $t \ge 1$, a subgraph $H$ is a \emph{$t$--spanner} of $G$ if the lengths of shortest paths in $G$ are preserved in $H$ up to a multiplicative factor of $t$. The \emph{subsetwise spanner} problem aims to…

Discrete Mathematics · Computer Science 2019-04-03 Reyan Ahmed , Keaton Hamm , Mohammad Javad Latifi Jebelli , Stephen Kobourov , Faryad Darabi Sahneh , Richard Spence

Signal processing on graph is attracting more and more attentions. For a graph signal in the low-frequency subspace, the missing data associated with unsampled vertices can be reconstructed through the sampled data by exploiting the…

Information Theory · Computer Science 2015-06-23 Xiaohan Wang , Pengfei Liu , Yuantao Gu

Error-correcting codes that admit local decoding and correcting algorithms have been the focus of much recent research due to their numerous theoretical and practical applications. An important goal is to obtain the best possible tradeoffs…

Data Structures and Algorithms · Computer Science 2018-09-19 Jeremiah Blocki , Venkata Gandikota , Elena Grigorescu , Samson Zhou

We study the spatial Gibbs random graphs introduced in [MV16] from the point of view of local convergence. These are random graphs embedded in an ambient space consisting of a line segment, defined through a probability measure that favors…

Probability · Mathematics 2017-12-12 Eric Ossami Endo , Daniel Valesin

An orthogonal representation of a graph $G$ over a field $\mathbb{F}$ is an assignment of a vector $u_v \in \mathbb{F}^t$ to every vertex $v$ of $G$, such that $\langle u_v,u_v \rangle \neq 0$ for every vertex $v$ and $\langle u_v,u_{v'}…

Combinatorics · Mathematics 2023-04-10 Inon Attias , Ishay Haviv

In this work we propose Lasagne, a methodology to learn locality and structure aware graph node embeddings in an unsupervised way. In particular, we show that the performance of existing random-walk based approaches depends strongly on the…

Social and Information Networks · Computer Science 2017-10-19 Evgeniy Faerman , Felix Borutta , Kimon Fountoulakis , Michael W. Mahoney

We prove that given any $\alpha$-approximation LOCAL algorithm for Minimum Dominating Set (MDS) on planar graphs, we can construct an $f(g)$-round $(3\alpha+1)$-approximation LOCAL algorithm for MDS on graphs embeddable in a given Euler…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-20 Marthe Bonamy , Avinandan Das , Cyril Gavoille , Timothé Picavet , Jukka Suomela , Alexandra Wesolek

We generalize the notion of an approximate indicator for a closed subgroup $H$ of a locally compact group $G$ introduced by Aristov, Runde, and Spronk and extend their characterization of the existence of such nets in terms of the…

Functional Analysis · Mathematics 2015-06-10 Zsolt Tanko

This paper presents a unified analysis framework that captures recent advances in the study of local-optimality characterizations for codes on graphs. These local-optimality characterizations are based on combinatorial structures embedded…

Information Theory · Computer Science 2012-08-15 Guy Even , Nissim Halabi

The task of finding an extension to a given partial drawing of a graph while adhering to constraints on the representation has been extensively studied in the literature, with well-known results providing efficient algorithms for…

Computational Geometry · Computer Science 2023-02-21 Sujoy Bhore , Robert Ganian , Liana Khazaliya , Fabrizio Montecchiani , Martin Nöllenburg

The diameter of a graph is one if its most important parameters, being used in many real-word applications. In particular, the diameter dictates how fast information can spread throughout data and communication networks. Thus, it is a…

Data Structures and Algorithms · Computer Science 2019-02-21 Keerti Choudhary , Omer Gold

Given an undirected $n$-node unweighted graph $G = (V, E)$, a spanner with stretch function $f(\cdot)$ is a subgraph $H\subseteq G$ such that, if two nodes are at distance $d$ in $G$, then they are at distance at most $f(d)$ in $H$.…

Data Structures and Algorithms · Computer Science 2013-01-11 Marek Cygan , Fabrizio Grandoni , Telikepalli Kavitha